Verified Job
IT / Software / Data Analyst
Senior Software Engineer Data Science
IT / Software / Data Analyst
#294374
Remote / WFH
Job Description
Data Science - Senior Engineer
About Us:
Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid - Buy Now, Pay Later. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners.
Skills that will help you succeed in this role:
5+ years of hands-on experience as a Data Science Engineer or similar role.
Expertise in visualizing and manipulating big datasets with spark.
Understanding of data modelling and software architecture and data platforms.
Experienced with modern tools for building ML pipelines, including data processing, training, inference and evaluation.Demonstrate effective coding, documentation, and communication habits
Technologies we work on:
ML Models Tabular on Xgboost, CatBoost, RF etc
Deep Learning for unstructured data. Partial RL(MAB) for online decision systems.
Distributed Model Training and Scoring on TFoS, TFJob, Spark ML etc. Big Data with PySpark pipelines.Git with CI and CD on Jenkins.
Deployment: Airflow, AWS(EMR or EKS) and Python.
Programming Languages; Python and SQL.
Responsibilities:
Data Systems : Exploring and visualizing data to gain an understanding of it. Verifying data quality, and/or ensuring it via data cleaning
Feature Engineering : Defining the pre-processing or feature engineering to be done on a given dataset. Defining data augmentation pipelines and feature quality systems.
Modelling: Design, develop, evaluate and deploy ML Systems that could be used to solve a given problem and ranking them by their success probability. Defining validation strategies. Analysing the errors of the model and designing strategies to overcome them.
Deployment and Evaluation : Develop and deploy machine learning applications according to the requirements of the production platform. Run machine learning tests and experiments. Evaluate production models for their performance, bias and drift. Focus on building ML Products than ML models.
Compensation:
If you are the right fit, we believe in creating wealth for you with enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it.
India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story
About Us:
Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. Paytm provides consumers with services like utility payments and money transfers, while empowering them to pay via Paytm Payment Instruments (PPI) like Paytm Wallet, Paytm UPI, Paytm Payments Bank Netbanking, Paytm FASTag and Paytm Postpaid - Buy Now, Pay Later. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners.
Skills that will help you succeed in this role:
5+ years of hands-on experience as a Data Science Engineer or similar role.
Expertise in visualizing and manipulating big datasets with spark.
Understanding of data modelling and software architecture and data platforms.
Experienced with modern tools for building ML pipelines, including data processing, training, inference and evaluation.Demonstrate effective coding, documentation, and communication habits
Technologies we work on:
ML Models Tabular on Xgboost, CatBoost, RF etc
Deep Learning for unstructured data. Partial RL(MAB) for online decision systems.
Distributed Model Training and Scoring on TFoS, TFJob, Spark ML etc. Big Data with PySpark pipelines.Git with CI and CD on Jenkins.
Deployment: Airflow, AWS(EMR or EKS) and Python.
Programming Languages; Python and SQL.
Responsibilities:
Data Systems : Exploring and visualizing data to gain an understanding of it. Verifying data quality, and/or ensuring it via data cleaning
Feature Engineering : Defining the pre-processing or feature engineering to be done on a given dataset. Defining data augmentation pipelines and feature quality systems.
Modelling: Design, develop, evaluate and deploy ML Systems that could be used to solve a given problem and ranking them by their success probability. Defining validation strategies. Analysing the errors of the model and designing strategies to overcome them.
Deployment and Evaluation : Develop and deploy machine learning applications according to the requirements of the production platform. Run machine learning tests and experiments. Evaluate production models for their performance, bias and drift. Focus on building ML Products than ML models.
Compensation:
If you are the right fit, we believe in creating wealth for you with enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it.
India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story
